We formulate a batch reinforcement learning-based demand response approach to prevent distribution network constraint violations in unknown grids. We use the...

Engineering design is often faced with uncertainties, making it difficult to determine an optimal design. In an unconstrained context, this amounts to choose...

The simultaneous stochastic optimization of mining complexes (SSOMC) is a large-scale stochastic combinatorial optimization problem that simultaneously manag...

Within a non-cooperative transboundary pollution dynamic game, we study the strategic impact of a region's investment in the adoption of a cleaner technolog...

A compact operations research (OR) model is proposed to analyse the prospects of meeting the Paris Agreement targets when direct air capture technologies can...

Thermostatically-controlled loads have a significant impact on electricity demand after service is restored following an outage, a phenomenon known as cold l...

With the ongoing energy transition, electric power and energy systems are becoming increasingly multi-dimensional and complex with higher levels of uncertain...

A piecewise constant Mayer cost function is used to model optimal control problems in which the state space is partitioned into several regions, each having ...

The use of space through satellites is more and more important for nations, companies, and individuals. However, since the first satellite was sent up in 19...

This paper presents an efficient method for extracting the second-order sensitivities from a system of implicit nonlinear equations. We design a custom aut...

The Tenth Montreal IPSW took place on August 13-27, 2020, and was jointly organized by the Centre de recherches mathématiques (CRM) and the Institute for Dat...

In this paper we examine the stability of international environmental agreements about a (common) emissions target. By signing the agreement, the parties d...

The increasingly complex energy systems are turning the attention towards model-free control approaches such as reinforcement learning (RL). This work propos...

This paper aims to identify the sources of value created in the strategic plan of a mining complex when the adaptive simultaneous stochastic optimization of ...

Stope design optimization defines mineable three-dimensional material volumes to be extracted from a mineral deposit, aiming to maximize cashflows subject ...

The geometallurgical models that predicting the throughput/comminution performance of the a processing plant often rely on rock hardness models, which are ba...

The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that sh...

In this paper, we apply flexibility-based operational planning method to microgrid (MG) unit commitment (UC). The problem is formulated based on model predi...

A new linear model is presented herein to optimize strategic production scheduling of an open pit mine with multiple processing streams while accounting for...

Geostatistically simulated representations of mineral deposits are used for resource/reserve assessments, mine design and production planning, project evalua...